Bank Churn - Profiling Report

Brought to you by YData

Dataset statistics

Number of variables	13
Number of observations	8000
Missing cells	5848
Missing cells (%)	5.6%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	1.9 MiB
Average record size in memory	243.2 B

Variable types

Numeric	6
Text	1
Categorical	6

Alerts

`Surname` has 409 (5.1%) missing values	Missing
`CreditScore` has 1641 (20.5%) missing values	Missing
`Balance` has 1615 (20.2%) missing values	Missing
`NumOfProducts` has 976 (12.2%) missing values	Missing
`HasCrCard` has 375 (4.7%) missing values	Missing
`EstimatedSalary` has 832 (10.4%) missing values	Missing
`CustomerId` has unique values	Unique
`Tenure` has 334 (4.2%) zeros	Zeros
`Balance` has 2283 (28.5%) zeros	Zeros

Reproduction

Analysis started	2025-11-19 21:17:17.252914
Analysis finished	2025-11-19 21:17:29.566078
Duration	12.31 seconds
Software version	ydata-profiling vv4.17.0
Download configuration	config.json

CustomerId
Real number (ℝ)

Unique

Distinct	8000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	15691188

Minimum	15565701
Maximum	15815690
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	62.6 KiB

Quantile statistics

Minimum	15565701
5-th percentile	15579208
Q1	15628960
median	15691115
Q3	15753728
95-th percentile	15802585
Maximum	15815690
Range	249989
Interquartile range (IQR)	124768

Descriptive statistics

Standard deviation	71872.267
Coefficient of variation (CV)	0.0045804221
Kurtosis	-1.1991968
Mean	15691188
Median Absolute Deviation (MAD)	62273
Skewness	-0.0013115379
Sum	1.2552951 × 10¹¹
Variance	5.1656227 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
15811261	1	< 0.1%
15567431	1	< 0.1%
15704795	1	< 0.1%
15592773	1	< 0.1%
15686219	1	< 0.1%
15763747	1	< 0.1%
15647975	1	< 0.1%
15734970	1	< 0.1%
15665283	1	< 0.1%
15607827	1	< 0.1%
Other values (7990)	7990	99.9%

Value	Count	Frequency (%)
15565701	1	< 0.1%
15565706	1	< 0.1%
15565796	1	< 0.1%
15565806	1	< 0.1%
15565879	1	< 0.1%
15565891	1	< 0.1%
15565996	1	< 0.1%
15566091	1	< 0.1%
15566111	1	< 0.1%
15566139	1	< 0.1%

Value	Count	Frequency (%)
15815690	1	< 0.1%
15815660	1	< 0.1%
15815656	1	< 0.1%
15815628	1	< 0.1%
15815626	1	< 0.1%
15815560	1	< 0.1%
15815530	1	< 0.1%
15815490	1	< 0.1%
15815443	1	< 0.1%
15815428	1	< 0.1%

Surname
Text

Missing

Distinct	2523
Distinct (%)	33.2%
Missing	409
Missing (%)	5.1%
Memory size	423.8 KiB

Length

Max length	23
Median length	16
Mean length	6.4327493
Min length	2

Characters and Unicode

Total characters	48831
Distinct characters	55
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1338 ?
Unique (%)	17.6%

Sample

1st row	Boone
2nd row	She
3rd row	Kerr
4th row	Loggia
5th row	Chiekwugo

Value	Count	Frequency (%)
scott	25	0.3%
lo	25	0.3%
brown	23	0.3%
martin	23	0.3%
smith	23	0.3%
yeh	22	0.3%
shih	21	0.3%
maclean	18	0.2%
johnson	18	0.2%
genovese	18	0.2%
Other values (2520)	7415	97.2%

Most occurring characters

Value	Count	Frequency (%)
a	4409	9.0%
e	4346	8.9%
n	3978	8.1%
o	3745	7.7%
i	3398	7.0%
r	2737	5.6%
l	2185	4.5%
s	1959	4.0%
u	1913	3.9%
h	1646	3.4%
Other values (45)	18515	37.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	48831	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	4409	9.0%
e	4346	8.9%
n	3978	8.1%
o	3745	7.7%
i	3398	7.0%
r	2737	5.6%
l	2185	4.5%
s	1959	4.0%
u	1913	3.9%
h	1646	3.4%
Other values (45)	18515	37.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	48831	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	4409	9.0%
e	4346	8.9%
n	3978	8.1%
o	3745	7.7%
i	3398	7.0%
r	2737	5.6%
l	2185	4.5%
s	1959	4.0%
u	1913	3.9%
h	1646	3.4%
Other values (45)	18515	37.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	48831	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	4409	9.0%
e	4346	8.9%
n	3978	8.1%
o	3745	7.7%
i	3398	7.0%
r	2737	5.6%
l	2185	4.5%
s	1959	4.0%
u	1913	3.9%
h	1646	3.4%
Other values (45)	18515	37.9%

CreditScore
Real number (ℝ)

Missing

Distinct	448
Distinct (%)	7.0%
Missing	1641
Missing (%)	20.5%
Infinite	0
Infinite (%)	0.0%
Mean	661.23526

Minimum	350
Maximum	850
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	62.6 KiB

Quantile statistics

Minimum	350
5-th percentile	500
Q1	595
median	664
Q3	729
95-th percentile	824
Maximum	850
Range	500
Interquartile range (IQR)	134

Descriptive statistics

Standard deviation	95.876126
Coefficient of variation (CV)	0.14499548
Kurtosis	-0.39748144
Mean	661.23526
Median Absolute Deviation (MAD)	67
Skewness	-0.1203844
Sum	4204795
Variance	9192.2315
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
850	187	2.3%
705	42	0.5%
678	42	0.5%
684	40	0.5%
667	39	0.5%
687	38	0.5%
655	36	0.4%
686	34	0.4%
652	34	0.4%
633	33	0.4%
Other values (438)	5834	72.9%
(Missing)	1641	20.5%

Value	Count	Frequency (%)
350	2	< 0.1%
351	1	< 0.1%
358	1	< 0.1%
363	1	< 0.1%
365	1	< 0.1%
367	1	< 0.1%
373	1	< 0.1%
376	2	< 0.1%
383	1	< 0.1%
401	1	< 0.1%

Value	Count	Frequency (%)
850	187	2.3%
849	7	0.1%
848	1	< 0.1%
847	4	0.1%
846	5	0.1%
845	4	0.1%
844	6	0.1%
843	2	< 0.1%
842	6	0.1%
841	10	0.1%

Geography
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	429.8 KiB

France	4030
Germany	1986
Spain	1984

Length

Max length	7
Median length	6
Mean length	6.00025
Min length	5

Characters and Unicode

Total characters	48002
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Germany
2nd row	France
3rd row	Spain
4th row	Germany
5th row	France

Common Values

Value	Count	Frequency (%)
France	4030	50.4%
Germany	1986	24.8%
Spain	1984	24.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
france	4030	50.4%
germany	1986	24.8%
spain	1984	24.8%

Most occurring characters

Value	Count	Frequency (%)
n	8000	16.7%
a	8000	16.7%
r	6016	12.5%
e	6016	12.5%
F	4030	8.4%
c	4030	8.4%
G	1986	4.1%
m	1986	4.1%
y	1986	4.1%
S	1984	4.1%
Other values (2)	3968	8.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	48002	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
n	8000	16.7%
a	8000	16.7%
r	6016	12.5%
e	6016	12.5%
F	4030	8.4%
c	4030	8.4%
G	1986	4.1%
m	1986	4.1%
y	1986	4.1%
S	1984	4.1%
Other values (2)	3968	8.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	48002	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
n	8000	16.7%
a	8000	16.7%
r	6016	12.5%
e	6016	12.5%
F	4030	8.4%
c	4030	8.4%
G	1986	4.1%
m	1986	4.1%
y	1986	4.1%
S	1984	4.1%
Other values (2)	3968	8.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	48002	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
n	8000	16.7%
a	8000	16.7%
r	6016	12.5%
e	6016	12.5%
F	4030	8.4%
c	4030	8.4%
G	1986	4.1%
m	1986	4.1%
y	1986	4.1%
S	1984	4.1%
Other values (2)	3968	8.3%

Gender
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	421.3 KiB

Male	4384
Female	3616

Length

Max length	6
Median length	4
Mean length	4.904
Min length	4

Characters and Unicode

Total characters	39232
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Male
2nd row	Female
3rd row	Male
4th row	Male
5th row	Male

Common Values

Value	Count	Frequency (%)
Male	4384	54.8%
Female	3616	45.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
male	4384	54.8%
female	3616	45.2%

Most occurring characters

Value	Count	Frequency (%)
e	11616	29.6%
a	8000	20.4%
l	8000	20.4%
M	4384	11.2%
F	3616	9.2%
m	3616	9.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	39232	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	11616	29.6%
a	8000	20.4%
l	8000	20.4%
M	4384	11.2%
F	3616	9.2%
m	3616	9.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	39232	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	11616	29.6%
a	8000	20.4%
l	8000	20.4%
M	4384	11.2%
F	3616	9.2%
m	3616	9.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	39232	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	11616	29.6%
a	8000	20.4%
l	8000	20.4%
M	4384	11.2%
F	3616	9.2%
m	3616	9.2%

Age
Real number (ℝ)

Distinct	69
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	38.935

Minimum	18
Maximum	92
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	62.6 KiB

Quantile statistics

Minimum	18
5-th percentile	25
Q1	32
median	37
Q3	44
95-th percentile	60
Maximum	92
Range	74
Interquartile range (IQR)	12

Descriptive statistics

Standard deviation	10.381389
Coefficient of variation (CV)	0.26663386
Kurtosis	1.3939202
Mean	38.935
Median Absolute Deviation (MAD)	6
Skewness	1.0060536
Sum	311480
Variance	107.77325
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
35	395	4.9%
37	388	4.9%
38	386	4.8%
34	363	4.5%
33	360	4.5%
36	357	4.5%
40	344	4.3%
39	343	4.3%
32	336	4.2%
31	303	3.8%
Other values (59)	4425	55.3%

Value	Count	Frequency (%)
18	15	0.2%
19	21	0.3%
20	31	0.4%
21	43	0.5%
22	62	0.8%
23	74	0.9%
24	107	1.3%
25	109	1.4%
26	164	2.1%
27	166	2.1%

Value	Count	Frequency (%)
92	1	< 0.1%
88	1	< 0.1%
84	1	< 0.1%
83	1	< 0.1%
82	1	< 0.1%
81	3	< 0.1%
80	3	< 0.1%
79	3	< 0.1%
78	5	0.1%
77	10	0.1%

Tenure
Real number (ℝ)

Zeros

Distinct	11
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.013875

Minimum	0
Maximum	10
Zeros	334
Zeros (%)	4.2%
Negative	0
Negative (%)	0.0%
Memory size	62.6 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	3
median	5
Q3	8
95-th percentile	9
Maximum	10
Range	10
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	2.8888104
Coefficient of variation (CV)	0.57616323
Kurtosis	-1.1575913
Mean	5.013875
Median Absolute Deviation (MAD)	2
Skewness	0.0064856405
Sum	40111
Variance	8.3452256
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
8	837	10.5%
1	832	10.4%
2	822	10.3%
5	819	10.2%
7	813	10.2%
4	810	10.1%
3	790	9.9%
6	779	9.7%
9	771	9.6%
10	393	4.9%

Value	Count	Frequency (%)
0	334	4.2%
1	832	10.4%
2	822	10.3%
3	790	9.9%
4	810	10.1%
5	819	10.2%
6	779	9.7%
7	813	10.2%
8	837	10.5%
9	771	9.6%

Value	Count	Frequency (%)
10	393	4.9%
9	771	9.6%
8	837	10.5%
7	813	10.2%
6	779	9.7%
5	819	10.2%
4	810	10.1%
3	790	9.9%
2	822	10.3%
1	832	10.4%

Balance
Real number (ℝ)

Missing Zeros

Distinct	4103
Distinct (%)	64.3%
Missing	1615
Missing (%)	20.2%
Infinite	0
Infinite (%)	0.0%
Mean	76929.669

Minimum	0
Maximum	250898.09
Zeros	2283
Zeros (%)	28.5%
Negative	0
Negative (%)	0.0%
Memory size	62.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	98009.13
Q3	127660.46
95-th percentile	162851.45
Maximum	250898.09
Range	250898.09
Interquartile range (IQR)	127660.46

Descriptive statistics

Standard deviation	62292.133
Coefficient of variation (CV)	0.80972834
Kurtosis	-1.4803442
Mean	76929.669
Median Absolute Deviation (MAD)	45635.03
Skewness	-0.15278862
Sum	4.9119594 × 10⁸
Variance	3.8803099 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2283	28.5%
106234.02	1	< 0.1%
62389.03	1	< 0.1%
100421.1	1	< 0.1%
133446.34	1	< 0.1%
87271.41	1	< 0.1%
52192.08	1	< 0.1%
98548.62	1	< 0.1%
121376.15	1	< 0.1%
55053.62	1	< 0.1%
Other values (4093)	4093	51.2%
(Missing)	1615	20.2%

Value	Count	Frequency (%)
0	2283	28.5%
3768.69	1	< 0.1%
12459.19	1	< 0.1%
14262.8	1	< 0.1%
16893.59	1	< 0.1%
27288.43	1	< 0.1%
28082.95	1	< 0.1%
28649.64	1	< 0.1%
29602.08	1	< 0.1%
33563.95	1	< 0.1%

Value	Count	Frequency (%)
250898.09	1	< 0.1%
238387.56	1	< 0.1%
216109.88	1	< 0.1%
212778.2	1	< 0.1%
212692.97	1	< 0.1%
210433.08	1	< 0.1%
209490.21	1	< 0.1%
207034.96	1	< 0.1%
206868.78	1	< 0.1%
206329.65	1	< 0.1%

NumOfProducts
Categorical

Missing

Distinct	4
Distinct (%)	0.1%
Missing	976
Missing (%)	12.2%
Memory size	410.2 KiB

1.0	3484
2.0	3323
3.0	183
4.0	34

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	21072
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	2.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	3484	43.5%
2.0	3323	41.5%
3.0	183	2.3%
4.0	34	0.4%
(Missing)	976	12.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	3484	49.6%
2.0	3323	47.3%
3.0	183	2.6%
4.0	34	0.5%

Most occurring characters

Value	Count	Frequency (%)
.	7024	33.3%
0	7024	33.3%
1	3484	16.5%
2	3323	15.8%
3	183	0.9%
4	34	0.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	21072	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	7024	33.3%
0	7024	33.3%
1	3484	16.5%
2	3323	15.8%
3	183	0.9%
4	34	0.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	21072	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	7024	33.3%
0	7024	33.3%
1	3484	16.5%
2	3323	15.8%
3	183	0.9%
4	34	0.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	21072	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	7024	33.3%
0	7024	33.3%
1	3484	16.5%
2	3323	15.8%
3	183	0.9%
4	34	0.2%

HasCrCard
Categorical

Missing

Distinct	2
Distinct (%)	< 0.1%
Missing	375
Missing (%)	4.7%
Memory size	407.8 KiB

1.0	5388
0.0	2237

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	22875
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	5388	67.3%
0.0	2237	28.0%
(Missing)	375	4.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	5388	70.7%
0.0	2237	29.3%

Most occurring characters

Value	Count	Frequency (%)
0	9862	43.1%
.	7625	33.3%
1	5388	23.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	22875	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	9862	43.1%
.	7625	33.3%
1	5388	23.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	22875	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	9862	43.1%
.	7625	33.3%
1	5388	23.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	22875	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	9862	43.1%
.	7625	33.3%
1	5388	23.6%

IsActiveMember
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	390.8 KiB

1	4108
0	3892

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	8000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
1	4108	51.3%
0	3892	48.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	4108	51.3%
0	3892	48.6%

Most occurring characters

Value	Count	Frequency (%)
1	4108	51.3%
0	3892	48.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	8000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	4108	51.3%
0	3892	48.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	8000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	4108	51.3%
0	3892	48.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	8000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	4108	51.3%
0	3892	48.6%

EstimatedSalary
Real number (ℝ)

Missing

Distinct	7167
Distinct (%)	> 99.9%
Missing	832
Missing (%)	10.4%
Infinite	0
Infinite (%)	0.0%
Mean	100057.17

Minimum	11.58
Maximum	199992.48
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	62.6 KiB

Quantile statistics

Minimum	11.58
5-th percentile	9817.0005
Q1	51545.353
median	100129.08
Q3	149216.32
95-th percentile	189984.9
Maximum	199992.48
Range	199980.9
Interquartile range (IQR)	97670.967

Descriptive statistics

Standard deviation	57441.733
Coefficient of variation (CV)	0.57408915
Kurtosis	-1.1790461
Mean	100057.17
Median Absolute Deviation (MAD)	48801.565
Skewness	0.002925442
Sum	7.1720976 × 10⁸
Variance	3.2995527 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
24924.92	2	< 0.1%
129956.13	1	< 0.1%
46172.47	1	< 0.1%
57553.98	1	< 0.1%
125979.36	1	< 0.1%
116124.28	1	< 0.1%
121440.8	1	< 0.1%
110932.24	1	< 0.1%
130686.59	1	< 0.1%
146371.72	1	< 0.1%
Other values (7157)	7157	89.5%
(Missing)	832	10.4%

Value	Count	Frequency (%)
11.58	1	< 0.1%
90.07	1	< 0.1%
91.75	1	< 0.1%
96.27	1	< 0.1%
142.81	1	< 0.1%
178.19	1	< 0.1%
236.45	1	< 0.1%
247.36	1	< 0.1%
287.99	1	< 0.1%
332.81	1	< 0.1%

Value	Count	Frequency (%)
199992.48	1	< 0.1%
199970.74	1	< 0.1%
199909.32	1	< 0.1%
199862.75	1	< 0.1%
199857.47	1	< 0.1%
199841.32	1	< 0.1%
199693.84	1	< 0.1%
199674.83	1	< 0.1%
199661.5	1	< 0.1%
199644.2	1	< 0.1%

Exited
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	390.8 KiB

0	6370
1	1630

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	8000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	6370	79.6%
1	1630	20.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	6370	79.6%
1	1630	20.4%

Most occurring characters

Value	Count	Frequency (%)
0	6370	79.6%
1	1630	20.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	8000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	6370	79.6%
1	1630	20.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	8000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	6370	79.6%
1	1630	20.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	8000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	6370	79.6%
1	1630	20.4%

	Age	Balance	CreditScore	CustomerId	EstimatedSalary	Exited	Gender	Geography	HasCrCard	IsActiveMember	NumOfProducts	Tenure
Age	1.000	0.026	-0.007	0.008	-0.001	0.373	0.020	0.047	0.018	0.145	0.097	-0.010
Balance	0.026	1.000	-0.005	-0.015	0.019	0.143	0.000	0.324	0.044	0.000	0.235	-0.004
CreditScore	-0.007	-0.005	1.000	0.018	-0.004	0.081	0.013	0.003	0.000	0.049	0.044	-0.002
CustomerId	0.008	-0.015	0.018	1.000	0.008	0.032	0.000	0.010	0.000	0.017	0.000	-0.025
EstimatedSalary	-0.001	0.019	-0.004	0.008	1.000	0.000	0.016	0.008	0.021	0.017	0.013	0.008
Exited	0.373	0.143	0.081	0.032	0.000	1.000	0.105	0.173	0.003	0.151	0.387	0.032
Gender	0.020	0.000	0.013	0.000	0.016	0.105	1.000	0.016	0.000	0.025	0.043	0.009
Geography	0.047	0.324	0.003	0.010	0.008	0.173	0.016	1.000	0.014	0.003	0.061	0.023
HasCrCard	0.018	0.044	0.000	0.000	0.021	0.003	0.000	0.014	1.000	0.000	0.000	0.039
IsActiveMember	0.145	0.000	0.049	0.017	0.017	0.151	0.025	0.003	0.000	1.000	0.040	0.027
NumOfProducts	0.097	0.235	0.044	0.000	0.013	0.387	0.043	0.061	0.000	0.040	1.000	0.035
Tenure	-0.010	-0.004	-0.002	-0.025	0.008	0.032	0.009	0.023	0.039	0.027	0.035	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

	CustomerId	Surname	CreditScore	Geography	Gender	Age	Tenure	Balance	NumOfProducts	HasCrCard	IsActiveMember	EstimatedSalary	Exited
0	15759244	Boone	687.0	Germany	Male	44	8	95368.14	2.0	1.0	1	1787.85	0
1	15725997	She	660.0	France	Female	35	6	100768.77	1.0	1.0	0	19199.61	0
2	15724296	Kerr	684.0	Spain	Male	41	2	119782.72	2.0	0.0	0	120284.67	0
3	15636820	Loggia	725.0	Germany	Male	40	8	104149.66	1.0	1.0	0	62027.90	0
4	15744529	Chiekwugo	510.0	France	Male	63	8	0.00	2.0	1.0	1	115291.86	0
5	15763907	Watts	820.0	France	Female	39	1	104614.29	1.0	1.0	0	61538.43	1
6	15671800	Robinson	688.0	France	Male	20	8	137624.40	2.0	1.0	1	197582.79	0
7	15567383	Slone	678.0	Germany	Female	44	2	98009.13	2.0	0.0	1	31384.86	0
8	15777179	Ellis	NaN	France	Male	35	9	NaN	2.0	0.0	1	NaN	0
9	15650391	NaN	633.0	France	Female	29	7	169988.35	1.0	1.0	0	4272.00	0

	CustomerId	Surname	CreditScore	Geography	Gender	Age	Tenure	Balance	NumOfProducts	HasCrCard	IsActiveMember	EstimatedSalary	Exited
7990	15775750	Yao	686.0	France	Male	37	9	134560.62	1.0	1.0	0	27596.39	0
7991	15735878	Law	850.0	Germany	Female	47	10	134381.52	NaN	0.0	0	26812.89	1
7992	15737509	Morrison	850.0	Spain	Male	34	8	NaN	1.0	0.0	0	NaN	0
7993	15782089	Mullen	NaN	France	Male	33	6	NaN	1.0	1.0	0	58458.26	0
7994	15663921	Pisani	429.0	France	Male	60	7	0.00	2.0	1.0	1	163691.48	0
7995	15628303	Thurgood	738.0	Spain	Male	35	3	0.00	1.0	1.0	1	15650.73	0
7996	15699225	Pirozzi	757.0	France	Male	46	0	0.00	2.0	1.0	0	37460.05	0
7997	15612525	Preston	NaN	France	Female	57	1	NaN	1.0	0.0	0	131372.38	1
7998	15724321	Baresi	516.0	Germany	Female	47	9	128298.74	1.0	0.0	0	149614.17	1
7999	15578761	Cunningham	NaN	Spain	Female	42	6	129634.25	NaN	1.0	1	177683.02	1

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)